Gen AI Course | Gen AI Tutorial For Beginners

This Gen AI tutorial for beginners is sort of like a Gen AI mini-course where a person can start learning the fundamentals of Gen AI and in the end, we build two end-to-end projects. Below is the outline of the exact topics that are covered.

00:00 Overview
00:29 What is Gen AI or Generative AI?
01:23 Gen AI evolution
10:00 What is LLM (Large Language Model)?
13:55 Embeddings, Vector Database
21:24 Retrieval Augmented Generation
28:16 Tooling for Gen AI
29:14 Langchain Fundamentals
1:14:49 End-to-End Project 1: Equity Research Tool
2:28:25 End-to-End Project 2: Retail Q&A Tool

#️⃣ Social Media #️⃣

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[codebasics]

OpenAI has stopped issuing few credits. You have two options (1) By spending less than 5$ on openai API, you can complete this project. You will learn a valuable skill by spending money that may be less than what you spend in a restaurant for a dinner. (2) Use LLama 3 etc open source model in groq.com or do the project using google gamma or palm models (the second project has relevant information on that).

[AI_Explore_Hub]

so far the best explanantion I heard on LLM. Thanks for all your hardwork in these videos.

[shashankshekharsingh]

sir your way of explaining things with examples is mindblowing, never seen anyone teaching like this before, absolutely amazed . thank you for this course 🙏🙏

[kjbkix]

Wow - you did such an awesome job producing this video! superb explanations and video production. Thanks for making this

[aditya]

I come from a Non-IT background and have found myself delving into the fascinating world of programming and cutting-edge technologies. Thanks to the invaluable guidance and tutorials by Dhawal Patel, I've been able to not only grasp but also teach Python, Java, and delve into complex domains like Machine Learning. Currently, my focus lies in research within bioinformatics, where I utilize deep learning and NLP techniques.

I owe a tremendous debt of gratitude to Dhawal Sir, whose teachings have been instrumental in shaping my journey. Without his insightful tutorials and unwavering support, I wouldn't have dared to dream of venturing into these domains. My deepest respect and appreciation go out to Dhawal Sir for his mentorship and guidance.

[DeepakVerma-wbjc]

This is the best course video I have watched on youtube on GenAI. Amazing work.

[sujeettean]

The finest explanation of LLM I've heard so far. I appreciate all of your efforts in making these videos. I am started learning the Gen AI.
Thanks😀

[yogeshbharadwaj]

Thanks for this detailed video sir.. this was my first video watching on GenAI, this video has given initial confidence about basic info already…Tks a ton 🙏

[tufail]

The way you explain everything thing more effectively is really good

[raminguyen]

Wowed. Thanks for your teaching. It is so useful for me. I have used generative AI for a long time, but your explaination makes me clarify my thoughts.

[nimishajaiswal]

This is an extremely informative video for GenAI, learning about LLMs, building connections with Python and creating our projects. Dhaval - you are a great teacher!

[abhinandanrao]

it was a fast track study. Great content !

[salwenikhil]

You are just awesome. Your teaching techniques are mindblowing i mean i dnt need to much stress my brain very smooth explanation awesome

[sqqicrx]

Hermano muy interesante, sigue adelante y agradecido por compartir tus conocimientos, saludos desde Peru!

[vimalrajayyappan]

Give this man a medal! Thank you! Very Intuitive! Fun and Clean, Crisp ! <3

[shreypatel]

Insanely Great Dhaval sir, waiting for more on Gen AI!

[AICoverBeats]

good work sir, even though my attention span is low, I was hooked to your video as I found it very interesting.

[jatulchaurasia]

00:01 Overview of Generative AI
02:31 Evolution from statistical ML to deep learning with neural networks
07:30 Transformers have led to a variety of powerful AI models.
09:59 Buddy is a stochastic parrot with mimicking ability and statistics-based predictions.
14:58 Understand Vector database and semantic search
17:21 Word to numeric representation using word embeddings
21:29 Retrieval Augmented Generation (RAG) allows fine-tuning or building AI models on specific data sets.
23:48 Using GPT-3 for querying data sources
28:24 To work with Gen AI, you need models, cloud services, and frameworks.
30:27 LLM based application using OpenAI API
34:36 Creating separate keys for different projects and managing them securely
36:55 Using LLM to generate creative restaurant names based on cuisine preferences.
41:33 Implementing Simple Sequential Chain concept in Gen AI Course
44:00 Using sequential chains to get both restaurant name and menu items in Gen AI Course
48:44 Setting up Streamlit for application development
51:15 Using response data to display restaurant name and menu items in UI
56:13 Practice coding while watching the video
58:22 Gen AI has a reasoning component for answering questions beyond its knowledge
1:02:48 Using Gen AI to retrieve information about Elon Musk's age in 2023
1:05:11 Initializing environment variables and using AI tools in an agent.
1:09:49 Using conversation chain to optimize cost and memory
1:12:15 Optimize OpenAI token cost by limiting conversational buffer memory
1:16:39 Research analysts provide detailed stock research for companies like Tata Motors and Reliance.
1:18:42 Importance of building a specialized tool over using Chat GPT
1:22:52 Using semantic search for finding relevant text chunks
1:24:56 Utilizing Vector databases for faster search and retrieval
1:29:05 Installing and loading Lang chain library in Jupyter notebook
1:31:39 Providing explanation about the movies.CSV file contents.
1:36:25 Text splitting and merging for efficient processing
1:38:35 Using Lang chain provides a simple API for text splitting.
1:43:22 Text splitting process using separators and size constraints
1:46:05 Gen AI Course explains recursive text splitter and merging for chunk optimization
1:50:23 Demonstration of using libraries to convert text into vectors
1:52:42 Using meditation and yoga to improve mental health with vector representation
1:57:30 Gen AI performs semantic search to provide results based on context, not just keywords
1:59:42 Retrieval QA with Sources Chain
2:04:06 Creating open API embeddings for document retrieval
2:06:39 Using a Vector database and creating a retrieval chain for text analysis.
2:11:06 Assembling the final project with pre-built individual pieces
2:13:10 Loading environment variables and creating basic UI in Gen AI module
2:18:20 Saving data in memory and displaying progress
2:20:46 Setting up Vector database and creating retrieval QA chain in Python
2:25:43 Automated news research tool for equity analysts
2:27:53 Utilizing vector databases for storing embeddings in large projects
2:32:07 Utilizing Google Palm and SQL Database Chain in Lang Chain Framework
2:34:10 Introduction to Vector Database and Google Palm for AI applications
2:38:14 Explaining the t-shirt records and database setup
2:40:45 Setting up a SQL database object with URI
2:45:40 Understanding the importance of correct database mapping for accurate results
2:48:17 Learning to run and manage queries in DB Chain
2:53:13 Summing of stock quantities for white color t-shirts
2:55:42 Storing data into arrays and using Hugging Face embedding for generating embeddings
3:00:34 Vector store converts input questions into embeddings for similarity matching.
3:02:52 Import SQL prompt template to generate queries.
3:07:42 Enhanced querying functionality with additional parameters
3:10:00 Creating a streamlit UI with few lines of code
3:14:54 Creating a main function in Python and running SQL queries in a database chain
3:17:27 Using Streamlet to ask and answer questions efficiently
Crafted by Merlin AI.

[kedargadgil]

Fantastic content and easy to follow. Well done!

[satyaprakashnayak]

56:34 Thanks for the tips. It was much needed.